Operational Monitoring and Forecasting of Land Surface Phenology from JPSS

VIIRS Observations and its Applications

Xiaoyang Zhang, Yunyue Yu, Lingling Liu, Yihua Wu, and

Michael Ek August 25, 2015

JPSS 2015 Annual Science Meeting

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Goal(s): To establish a system for monitoring in real-time and

forecasting in short term temporal development of vegetation growth in North America and across the globe from JPSS VIIRS.

Targeted users: Numerical Weather Prediction Systems at NOAA Environmental

Modeling Center Agriculture and forest management Climate monitoring

Objectives

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Metrics of Land Surface Phenology/Dynamics

1. Onset of greenness increase 2. Onset of greenness maximum 3. Onset of greenness decrease 4. Onset of greenness minimum 5. Growing season VI minimum 6. Growing season VI maximum 7. Summation of VI for growing season length 8. Rate of change in greenness increase; 9. Rate of change in greenness decrease 10. Onset of fall foliage low coloration 11. Onset of fall foliage moderate coloration 12. Onset of fall foliage near peak coloration 13. Onset of fall foliage peak coloration 14. Onset of fall foliage post peak coloration

Put one figure here

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Real Time phenology is detected from currently available time series of satellite data without any latency

Establishment of Phenology Climate Data Record and Detection of Real Time Phenology

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Climate data record of phenology is detected from annual time series of satellite data with a latency longer than half year

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Prediction of Temporal Greenness Trajectory in Autumn

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A set of potential VI trajectories in a senescent phase are modeled in near-real time for a pixel from the available observations (dots) and climatology.

P

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Prediction of Temporal Greenness Trajectory in Spring

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Simulating the potential temporal trajectory from available daily VI data (circles) and monitoring and forecasting phenological events in spring green-up phase.

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Biophysically Understanding Temporal Trajectory of Satellite Vegetation Index (VI)

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Calibration of Climatological Phenology Trajectory (from MODIS) to be comparable

with VIIRS Data

MODIS EVI and VIIRS EVI are not exactly the same

Climatological EVI from MODIS needs to be calibrated to be comparable to VIIRS EVI

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Climatological MODIS Vegetation Index for Real-time Monitoring from VIIRS

data

Climatology MODIS vegetation index (2001-2012) calibrated using annual time series of MODIS and VIIRS data in 2013.

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Climatology of Dormancy Onset and Standard Variation

Climatology from MODIS data from 2001-2012

Standard variation of dormancy onset (2001-2012)

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Real-time Monitoring and Short-term Forecasting of Fall Foliage from JPSS

VIIRS

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Uncertainty of Color Foliage Monitoring

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Monitoring and Forecasting of Spring Vegetation Progress

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VIIRS Monitoring Across North America

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Service Public Interests

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Fall Foliage Monitoring from NOAA National Weather Service Weather Forecast Office

VIIRS real time monitoring of fall foliage coloration can serve the prediction from weather data in NOAA National Weather Service.

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Real Time Phenology for Land Modeling (in NOAA EMC)

Climatology greenness currently used in Land Model in EMC

Metrics of phenology – the seasonal vegetation dynamics • Estimate surface energy balance, • Determine the partition of surface sensible and latent heat fluxes • Predict boundary layer structures in the global and regional numerical

weather prediction models

Real Time VIIRS data from phenological detection

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Assistance in USA National Phenology Network

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Serving Crop Progress Monitoring

2015

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Climate Indicator – Spring 2015

Real time monitoring shows a earlier spring in the western region than eastern area in 2015

Comparison of the spring event in 2015 with climatology (2000-2011) shows the spring was advanced in western region while it was delayed in eastern area.

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Summary and Issues

1. Near real time VIIRS observations make it possible to reconstruct the potential trajectories of daily vegetation dynamics timely.

2. The preliminary results indicate VIIRS real-time monitoring of phenology has wide applications.

3. This project has been very successful with the support from JPSS Risk Reduction during the past two years.

4. How to continue this effort is a major issue because the funding support will end before next summer.